Emission inventories are important for both simulating pollutant concentrations and designing emission mitigation policies. Ho Chi Minh City (HCMC) is the biggest city in Vietnam but lacks an updated spatial emission inventory (EI). In this study, we propose a new approach to update and improve a comprehensive spatial EI for major short-lived climate pollutants (SLCPs) and greenhouse gases (GHGs) (SO.sub.2, NO.sub.x, CO, non-methane volatile organic compounds (NMVOCs), PM.sub.10, PM.sub.2.5, black carbon (BC), organic carbon (OC), NH.sub.3, CH.sub.4, N.sub.2 O and CO.sub.2). Our originality is the use of satellite-derived urban land use morphological maps which allow spatial disaggregation of emissions. We investigated the possibility of using freely available coarse-resolution satellite-derived digital surface models (DSMs) to estimate building height. Building height is combined with urban built-up area classified from Landsat images and nighttime light data to generate annual urban morphological maps. With outstanding advantages of these remote sensing data, our novel method is expected to make a major improvement in comparison with conventional allocation methodologies such as those based on population data. A comparable and consistent local emission inventory (EI) for HCMC has been prepared, including three key sectors, as a successor of previous EIs. It provides annual emissions of transportation, manufacturing industries, and construction and residential sectors at 1 km resolution. The target years are from 2009 to 2016. We consider both Scope 1, all direct emissions from the activities occurring within the city, and Scope 2, that is indirect emissions from electricity purchased. The transportation sector was found to be the most dominant emission sector in HCMC followed by manufacturing industries and residential area, responsible for over 682 Gg CO, 84.8 Gg NO.sub.x, 20.4 Gg PM.sub.10 and 22 000 Gg CO.sub.2 emitted in 2016. Due to a sharp rise in vehicle population, CO, NO.sub.x, SO.sub.2 and CO.sub.2 traffic emissions show increases of 80 %, 160 %, 150 % and 103 % respectively between 2009 and 2016. Among five vehicle types, motorcycles contributed around 95 % to total CO emission, 14 % to total NO.sub.x emission and 50 %-60 % to CO.sub.2 emission. Heavy-duty vehicles are the biggest emission source of NO.sub.x, SO.sub.2 and particulate matter (PM) while personal cars are the largest contributors to NMVOCs and CO.sub.2 . Electricity consumption accounts for the majority of emissions from manufacturing industries and residential sectors. We also found that Scope 2 emissions from manufacturing industries and residential areas in 2016 increased by 87 % and 45 %, respectively, in comparison with 2009. Spatial emission disaggregation reveals that emission hotspots are found in central business districts like Quan 1, Quan 4 and Quan 7, where emissions can be over 1900 times those estimated for suburban HCMC. Our estimates show relative agreement with several local inherent EIs, in terms of total amount of emission and sharing ratio among elements of EI. However, the big gap was observed when comparing with REASv2.1, a regional EI, which mainly applied national statistical data. This publication provides not only an approach for updating and improving the local EI but also a novel method of spatial allocation of emissions on the city scale using available data sources.